11 research outputs found
Adaptive resource optimization for edge inference with goal-oriented communications
AbstractGoal-oriented communications represent an emerging paradigm for efficient and reliable learning at the wireless edge, where only the information relevant for the specific learning task is transmitted to perform inference and/or training. The aim of this paper is to introduce a novel system design and algorithmic framework to enable goal-oriented communications. Specifically, inspired by the information bottleneck principle and targeting an image classification task, we dynamically change the size of the data to be transmitted by exploiting banks of convolutional encoders at the device in order to extract meaningful and parsimonious data features in a totally adaptive and goal-oriented fashion. Exploiting knowledge of the system conditions, such as the channel state and the computation load, such features are dynamically transmitted to an edge server that takes the final decision, based on a proper convolutional classifier. Hinging on Lyapunov stochastic optimization, we devise a novel algorithmic framework that dynamically and jointly optimizes communication, computation, and the convolutional encoder classifier, in order to strike a desired trade-off between energy, latency, and accuracy of the edge learning task. Several simulation results illustrate the effectiveness of the proposed strategy for edge learning with goal-oriented communications
A Survey on Semantic Communications for Intelligent Wireless Networks
With deployment of 6G technology, it is envisioned that competitive edge of
wireless networks will be sustained and next decade's communication
requirements will be stratified. Also 6G will aim to aid development of a human
society which is ubiquitous and mobile, simultaneously providing solutions to
key challenges such as, coverage, capacity, etc. In addition, 6G will focus on
providing intelligent use-cases and applications using higher data-rates over
mill-meter waves and Tera-Hertz frequency. However, at higher frequencies
multiple non-desired phenomena such as atmospheric absorption, blocking, etc.,
occur which create a bottleneck owing to resource (spectrum and energy)
scarcity. Hence, following same trend of making efforts towards reproducing at
receiver, exact information which was sent by transmitter, will result in a
never ending need for higher bandwidth. A possible solution to such a challenge
lies in semantic communications which focuses on meaning (context) of received
data as opposed to only reproducing correct transmitted data. This in turn will
require less bandwidth, and will reduce bottleneck due to various undesired
phenomenon. In this respect, current article presents a detailed survey on
recent technological trends in regard to semantic communications for
intelligent wireless networks. We focus on semantic communications architecture
including model, and source and channel coding. Next, we detail cross-layer
interaction, and various goal-oriented communication applications. We also
present overall semantic communications trends in detail, and identify
challenges which need timely solutions before practical implementation of
semantic communications within 6G wireless technology. Our survey article is an
attempt to significantly contribute towards initiating future research
directions in area of semantic communications for intelligent 6G wireless
networks